MRI (magnetic resonance imaging) is a noninvasive method for imaging that produces images of the anatomy and the functional condition of the human body. An MRI scanner is capable of acquiring two-dimensional (2-D) sectional images (slices) of the human body from any orientation. Unlike other diagnostic imaging methods, MRI does not use ionizing radiation. Instead, MRI operates with signals in the radio-frequency (RF) range; MR signals used for generating image slices come from the body itself.
MR images are rich in information. MR image characteristics are intrinsically related to operator-specific parameters, termed MRI protocols, and tissue properties, including the proton density δ, spin-lattice relaxation time T1, the spin-spin relaxation time T2, molecular motions such as diffusion and perfusion, susceptibility, and chemical shift differences.
The MR image is stored and presented as an array of voxels, that is, as volume pixel data. With voxel data, image data values can be represented in three-dimensional space. This feature offers enhanced opportunities for improved visualization and display and can be particularly advantageous to a diagnostician in examining images of the internal anatomy of a patient.
Although there may be advantages when compared against other imaging techniques, MRI provides a relatively limited image resolution. Currently, in-plane MRI slice resolution is higher than out-of-plane resolution, with the former being fundamentally limited by the Fourier pixel size and the latter limited by the available gradient strength and the allowable pulse length. Typical in-plane resolution for a clinical MR image is in the range of 350 microns. Out-of-plane resolution is typically 14 times lower (coarser), in the range of about 4 mm.
In general, spatial resolution of an imaging system is related to its point spread function (PSF). For example, two point sources are resolvable in the resultant image only when the separation between them is larger than the width at the half maximum of the PSF. Symbolically, this is the convolution expressed by{circumflex over (I)}(x)=I(x)*h(x),  (1)which describes an elegant mathematical relationship between an object function I(x), its image Î(x), and the PSF function h(x).
Improvements to MR image resolution are desirable. However, increasing voxel resolution in MR images using existing image acquisition methods has proved to be particularly challenging. Adapting conventional imaging techniques to obtain full scans in three dimensions can be very time consuming, thus significantly extending acquisition times.
Super-resolution (SR) techniques for improving MRI resolution have attracted attention from researchers in diagnostic imaging fields. However, the adaptation of such techniques is not straightforward and conventional approaches to increasing resolution have thus far have generally proved unsatisfactory. SR methods based on Fourier Transform theory and the frequency domain, for example, do not appear to handle image blurring or alignment particularly well. Existing techniques are sensitive to partial volume effects (PVEs) that result from limited spatial resolution. PVEs obscure 3-D renderings and compromise clear depiction of tissue boundaries, especially when these boundaries are oriented parallel to the acquisition plane. Other conventional approaches, such as the method described in U.S. Pat. No. 6,998,841 entitled “Method and System which Forms an Isotropic, High-Resolution, Three-Dimensional Diagnostic Image of a Subject from Two-Dimensional Image Data Scans” to Tamez-Pena et al. require that the different images that are combined or fused to form an enhanced 3-D image need to be substantially orthogonal with respect to each other, which places some constraints on imaging techniques and limits the usability of the SR algorithms.
Thus, it can be seen that although there have been a number of proposed approaches for improving the voxel resolution of MRI images, there remains room for improvement in image processing techniques.